What Is Bidirectional Graph in Data Structure?


Scott Campbell

A bidirectional graph is a type of graph that allows traversal in both directions. In other words, it is possible to move from one vertex to another either through an outgoing edge or an incoming edge. This versatility makes bidirectional graphs particularly useful in certain applications.

Representation of Bidirectional Graphs

There are several ways to represent a bidirectional graph in data structures. One common approach is to use an adjacency list, where each vertex stores a list of its neighboring vertices. However, in the case of a bidirectional graph, each vertex needs to store both its outgoing neighbors and its incoming neighbors.

To illustrate this concept, let’s consider an example of a bidirectional graph representing friendships between people. Each person can have friends they are connected to and friends who are connected to them. This scenario perfectly fits the characteristics of a bidirectional graph.

Traversing a Bidirectional Graph

Traversing a bidirectional graph involves visiting each vertex and exploring its adjacent vertices in both directions. There are various algorithms that can be used for this purpose.

Breadth-First Search (BFS)

BFS is commonly used for traversing graphs, including bidirectional graphs. It starts at an initial vertex and explores all its neighboring vertices before moving on to the next level of vertices. By considering both incoming and outgoing edges, BFS can uncover the shortest path between two vertices efficiently.

  • Step 1: Start with an initial vertex.
  • Step 2: Enqueue the initial vertex.
  • Step 3: Dequeue a vertex and mark it as visited.
  • Step 4: Explore its adjacent vertices (both incoming and outgoing) and enqueue them if they haven’t been visited.
  • Step 5: Repeat steps 3 and 4 until the queue is empty.

Depth-First Search (DFS)

DFS is another algorithm commonly used for traversing graphs, including bidirectional graphs. It explores as far as possible along each branch before backtracking. Although DFS does not guarantee the shortest path between two vertices, it can be useful for certain scenarios.

  • Step 2: Mark the initial vertex as visited.
  • Step 3: Explore its adjacent vertices (both incoming and outgoing) that haven’t been visited.
  • Step 4: Recursively apply steps 2 and 3 to each unvisited adjacent vertex.
  • Applications of Bidirectional Graphs

    Bidirectional graphs find applications in various domains, including social networks, traffic routing systems, recommendation systems, and more. The ability to traverse in both directions allows for efficient analysis of relationships between entities and the discovery of meaningful patterns.

    In a social network context, bidirectional graphs can help identify mutual friendships, explore communities, detect influential individuals, and analyze information flow between users. Similarly, in traffic routing systems, bidirectional graphs can optimize routes by considering both incoming and outgoing traffic flow on roads or highways.

    In Conclusion

    Bidirectional graphs are a valuable tool in data structures that enable traversal in both directions. They can be represented using adjacency lists or other suitable data structures.

    Algorithms such as BFS and DFS can be utilized to explore bidirectional graphs efficiently. Understanding bidirectional graphs and their applications can greatly enhance problem-solving capabilities in various domains.

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